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Semantic audio content-based music recommendation and visualization based on user preference examples

Dmitry Bogdanov, Martín Haro, Ferdinand Fuhrmann, Anna Xambó, Emilia Gómez, Perfecto Herrera
2013 Information Processing & Management  
Semantic audio content-based music recommendation and visualization based on user preference examples.  ...  In the first one, we consider three approaches to music recommendation, two of them based on a semantic music similarity measure, and one based on a semantic probabilistic model.  ...  Acknowledgements The authors thank all participants involved in the evaluation and Justin Salamon for proofreading.  ... 
doi:10.1016/j.ipm.2012.06.004 fatcat:y6bcjarzandwljl5qxqruv5yh4

A content-based system for music recommendation and visualization of user preferences working on semantic notions

Dmitry Bogdanov, Martin Haro, Ferdinand Fuhrmann
2011 2011 9th International Workshop on Content-Based Multimedia Indexing (CBMI)  
Using these services, the system retrieves a set of tracks preferred by a user, and further computes a semantic description of musical preferences based on raw audio information.  ...  Thereafter, the system generates music recommendations, using a semantic music similarity measure, and a user's preference visualization, mapping semantic descriptors to visual elements.  ...  Here, content-based information extracted from audio can help to overcome this problem [6, 1] . In this work, we present a system for music recommendation and visualization of user preferences.  ... 
doi:10.1109/cbmi.2011.5972554 dblp:conf/cbmi/BogdanovHFXGH11 fatcat:qyardjwo2jcxhf5ddov44ifo4u

Content-Based Multimedia Recommendation Systems: Definition and Application Domains

Yashar Deldjoo, Markus Schedl, Paolo Cremonesi, Gabriella Pasi
2018 Italian Information Retrieval Workshop  
The goal of this work is to formally provide a general definition of a multimedia recommendation system (MMRS), in particular a content-based MMRS (CB-MMRS), and to shed light on different applications  ...  of multimedia content for solving a variety of tasks related to recommendation.  ...  In CB-MMRS, the media types constituting both the input and the output of the system are the same (e.g., music recommendation based on music acoustic content plus target users' preferences); However in  ... 
dblp:conf/iir/DeldjooSCP18 fatcat:guhkkc7zqvahxfu6oabatyl6xe

Enhancing Video Recommendation Using Multimedia Content [chapter]

Yashar Deldjoo
2019 SpringerBriefs in Applied Sciences and Technology  
The information obtained from multimedia content and learning from muli-modal sources (e.g., audio, visual and metadata) on the other hand, offers the possibility of uncovering relationships between modalities  ...  user-generated tags) at their core since they are human-generated and are assumed to cover the 'content semantics' of movies by a great degree.  ...  after watching the corresponding movie trailer in which the visual content (e.g., color, lighting, motion) and the audio content (e.g., music or spoken dialogues) play a key role in users' perceived affinity  ... 
doi:10.1007/978-3-030-32094-2_6 fatcat:ejusjykphfbe3jwes6u3r55uxe

Foafing The Music: A Music Recommendation System Based On Rss Feeds And User Preferences

Òscar Celma, Miquel Ramírez, Perfecto Herrera
2005 Zenodo  
from music related RSS feeds-, and content-based descriptions -extracted from the audio itself. 4.  ...  These services are meant for "home" users, music content producers and distributors, and academic users. One special feature is that these descriptions are composed by semantic descriptors.  ... 
doi:10.5281/zenodo.1414800 fatcat:bpqxjhafgnay3kw4xeh2nub3vi

Intelligent User Interfaces for Music Discovery: The Past 20 Years and What's to Come

Peter Knees, Markus Schedl, Masataka Goto
2019 Zenodo  
web platforms, the exploitation of user-generated metadata pertaining to semantic descriptions; and third, connected to streaming services, the collection of online music interaction traces on a large  ...  , intelligent audio processing and content description algorithms that facilitate the automatic organization of repositories and finding music according to sound qualities; second, connected to collective  ...  Moodplay [1] is an interactive music recommender system that uses a hybrid recommendation algorithm based on mood metadata and audio content.  ... 
doi:10.5281/zenodo.3527737 fatcat:kaj6hodbfjdyhodl5avk2ciloq

Content-based Music Recommendation: Evolution, State of the Art, and Challenges [article]

Yashar Deldjoo, Markus Schedl, Peter Knees
2021 arXiv   pre-print
content, user-generated content, and derivative content.  ...  In contrast to most other recommendation domains, which predominantly rely on collaborative filtering (CF) techniques, music recommenders have traditionally embraced content-based (CB) approaches.  ...  We, therefore, review research that creates and visualizes different explanations based on the users' or items' neighbors, on content features, on context, and audio. (3) Accomplishing context-awareness  ... 
arXiv:2107.11803v1 fatcat:4hz4hqkkmvcapbdr3wvtp2t4iu

Intelligent User Interfaces for Music Discovery

Peter Knees, Markus Schedl, Masataka Goto
2020 Transactions of the International Society for Music Information Retrieval  
Phase 1 has seen the development of content-based music retrieval interfaces built upon audio processing and content description algorithms facilitating the automatic organization of repositories and finding  ...  Phase 2 comprises interfaces incorporating collaborative and automatic semantic description of music, exploiting knowledge captured in user-generated metadata.  ...  MoodPlay by Andjelkovic et al. (2019) is an interactive music recommender system that uses a hybrid recommendation algorithm based on mood metadata and audio content, cf. Section 2.1.  ... 
doi:10.5334/tismir.60 fatcat:clhfsnzwxzgu3bjtkxf3fyws7u

Foafing the Music: Bridging the Semantic Gap in Music Recommendation [chapter]

Òscar Celma
2006 Lecture Notes in Computer Science  
The system uses the Friend of a Friend (FOAF) and RDF Site Summary (RSS) vocabularies for recommending music to a user, depending on the user's musical tastes and listening habits.  ...  The presented system provides music discovery by means of: user profiling (defined in the user's FOAF description), context based information (extracted from music related RSS feeds) and content based  ...  Acknowledgements This work is partially funded by the SIMAC IST-FP6-507142, and the SALERO IST-FP6-027122 European projects.  ... 
doi:10.1007/11926078_67 fatcat:4bfulz5pnndthmcfe6fnalyv6i

Music Recommendation: A multi-faceted approach

Oscar Celma, Xavier Serra
2006 Zenodo  
As a test–bed example, two prototypes have been developed a music search engine and music discovery based on music similarity, and a hybrid music recommender.  ...  Music recommendation involves the modelling of user preferences, as well as the matching between profiles and music related information.  ...  Content-based filtering In the content-based (CB) filtering approach, the recommender collects information describing the items and then, based on the user's preferences, it predicts which items the user  ... 
doi:10.5281/zenodo.3743108 fatcat:wcfdl34jnzeqtmzjzamjjvdt44

Intelligent broadcasting system and services for personalized semantic contents consumption

Sung Ho Jin, Tae Meon Bae, Yong Man Ro, Hoi-Rin Kim, Munchurl Kim
2006 Expert systems with applications  
For content-level services, real-time content filtering, personalized video skimming, and content-based retrieval using audio characteristic are implemented.  ...  In this paper, an intelligent broadcasting system for enhanced personalized-services, based on the semantics of broadcasting contents, is proposed.  ...  Acknowledgements We would like to thank Mr Sungtak Kim, Mr Jun Ho Cho, and Mr Mun Jo Kim who participated in this project.  ... 
doi:10.1016/j.eswa.2005.09.021 fatcat:lvwqylpk2vc3tm3uiq54xsroiy

User-Aware Music Retrieval

Markus Schedl, Sebastian Stober, Emilia Gómez, Nicola Orio, Cynthia C.S. Liem, Marc Herbstritt
2012 Dagstuhl Publications  
We then propose and discuss various requirements for a personalized, user-aware music retrieval system.  ...  Particularly focusing on the music domain, this article gives an overview of different aspects we deem important to build personalized music retrieval systems.  ...  Using these services, the system retrieves a set of tracks preferred by a user, and further tries to infer a semantic description of musical preferences from raw audio information.  ... 
doi:10.4230/dfu.vol3.11041.135 dblp:conf/dagstuhl/SchedlSGOL12 fatcat:weo2yddzzrfwjkgmfk7zrs3apy

How Much Metadata Do We Need In Music Recommendation? A Subjective Evaluation Using Preference Sets

Dmitry Bogdanov, Perfecto Herrera
2011 Zenodo  
This research has been partially funded by the FI Grant of Generalitat de Catalunya (AGAUR) and the Buscamedia (CEN-20091026), Classical Planet (TSI-070100-2009-407, MITYC), and DRIMS (TIN2009-14247-C02  ...  Such an explicit strategy was shown to capture the essence of users' musical preferences being suitable for preference visualization and distance-based music recommendation.  ...  systems, which are able to facilitate music search and retrieval based on aggregated user profiles, or simple queries-by-example specified by users.  ... 
doi:10.5281/zenodo.1415103 fatcat:i3w5zpd6dbcsbenxjriq4q3f4i

Music Data Analysis: A State-of-the-art Survey [article]

Shubhanshu Gupta
2014 arXiv   pre-print
This is reflected by wide array of alternatives offered in music related web/mobile apps, information portals, featuring millions of artists, songs and events attracting user activity at similar scale.  ...  Various approaches involving machine learning, information theory, social network analysis, semantic web and linked open data are represented in the form of taxonomy along with data sources and use cases  ...  Rather than going with conventional music recommendation practices like collaborative filtering (recommending music to a user based on the stated tastes of other related users), content-based, and recommendation  ... 
arXiv:1411.5014v1 fatcat:jdck4wqwo5clzlb4b2kzoxlhsy

A Multimodal Fusion Online Music Education System for Universities

Peng Liu, Yixiao Cao, Lei Wang, Qiangyi Li
2022 Computational Intelligence and Neuroscience  
A personalized learning strategy based on users' interest is proposed through the mining of online education data, and a music online education system has been developed on this basis.  ...  To improve the recommendation accuracy of the model, an embedding propagation knowledge graph recommendation method based on decay factors is proposed.  ...  Acknowledgments is work was supported by the Music College, Cangzhou Normal University, Art Department, Criminal Investigation Police University of China.  ... 
doi:10.1155/2022/6529110 pmid:35983155 pmcid:PMC9381263 fatcat:kdy2tsdn3rfi5o4uow3wgmgpde
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